ArticleSystems and synthetic biology2011
In silico description of cobalt and nickel assimilation systems in the genomes of methanogens.
Article in Systems and synthetic biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 12 citations in OpenAlex.
- Anaerobic reduction of europium by a Clostridium strain as a strategy for rare earth biorecovery.Scientific reports · 2019Article
- Kinetic modeling of Stickland reactions-coupled methanogenesis for a methanogenic culture.AMB Express · 2019Article
- Reduction of hexavalent chromium by the thermophilic methanogenGeochimica et cosmochimica acta · 2015Article
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1 author at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Methanogens are a diverse group of organisms that can live in a wide range of environments. Herein, cobalt and tungsten assimilation pathways have proposed to be established in the genomes of Methanococcus maripaludies C5 and Methanosarcina mazei Go1, respectively. All of the proteins involved in the proposed pathways were identified from public domain databases and then complied manually to reconstruct the pathways. The function of proteins with unknown function was assigned by a combined prediction approach. Totally, 17 proteins were identified to cobalt transport and assimilation processes whereas 7 proteins reported to tungsten assimilation system. Phylogenetic analysis of this study revealed that heavy metal transporter of methanogens could be evolved from closely related members in the different genera of methanogens. Nevertheless, genes encoding for metal resistance proteins could be originated from thermophilic and sulfur reducing bacteria. Many metalloenzymes in methanogens were very unique to the species of methanogens. It implied that these metal ions were utilized to produce the precursors for energy driven processes of methanogens. This study suggested that in combination of systems models and evolutionary inference can only correlate metabolic fluxes and physiological changes in methanogens. In silico models of this study will provide insights to design experiments for heavy metal assimilation processes of methanogens growing under heavy metal-rich environments and or in a laboratory condition.
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